Description
This .zip file contains the pre-trained weights for the MaD TwinNet. In order to use them, you need the code of MaD TwinNet (available from here). Code of MaD TwinNet is based on PyTorch framework. All weights are serialized (i.e. saved to hard disk) to the disk using Python 3.6v pickle package and protocol=2 Note bold: Software license of the MaD TwinNet code is also applied to these pre-trained weights.
| Date made available | 2 Feb 2018 |
|---|---|
| Publisher | Zenodo |
Field of science, Statistics Finland
- 113 Computer and information sciences
Research output
- 1 Conference contribution
-
MaD TwinNet: Masker-Denoiser Architecture with Twin Networks for Monaural Sound Source Separation
Drossos, K., Mimilakis, S. I., Serdyuk, D., Schuller, G., Virtanen, T. & Bengio, Y., 10 Jul 2018, 2018 International Joint Conference on Neural Networks (IJCNN). IEEEResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
19 Citations (Scopus)
Datasets
-
MaD TwinNet Results (SDR, SIR, and SAR)
Drossos, K. (Creator), Mimilakis, S. I. (Creator), Serdyuk, D. (Creator), Schuller, G. (Creator), Virtanen, T. (Creator) & Bengio, Y. (Creator), Zenodo, 2 Feb 2018
Dataset
Cite this
- DataSetCite